title: Assessing depression symptoms in those with insomnia: an examination of the beck depression inventory second edition (BDI-II).
abstract: BACKGROUND
  Due to concerns about overlapping symptomatology between medical conditions and depression, the validity of the beck depression inventory (BDI-II) has been assessed in various medical populations. Although major depressive disorder (MDD) and primary insomnia (PI) share some daytime symptoms, the BDI-II has not been evaluated for use with insomnia patients.
  
  
  METHODS
  Participants (N=140) were screened for the presence of insomnia using the Duke structured clinical interview for sleep disorders (DSISD), and evaluated for diagnosis of MDD using the structured clinical interview for DSM-IV-TR (SCID). Participants' mean BDI-II item responses were compared across two groups [insomnia with or without MDD) using multivariate analysis of variance (MANOVA), and the accuracy rates of suggested clinical cutoffs for the BDI-II were evaluated using a receiver operating characteristic (ROC) curve analysis.
  
  
  RESULTS
  The insomnia with depression group had significantly higher scores on several items; however, the groups did not differ on insomnia, fatigue, concentration problems, irritability, libido, increased appetite, and thoughts relating to suicide, self-criticism and punishment items. The ROC curve analysis revealed moderate accuracy for the BDI-II's identification of depression in those with insomnia. The suggested BDI cutoff of >or=17 had 81% sensitivity and 79% specificity. Use of the mild cutoff for depression (>or=14) had high sensitivity (91%) but poor specificity (66%).
  
  
  CONCLUSIONS
  Several items on the BDI-II might reflect sleep disturbance symptoms rather than depression per se. The recommended BDI-II cutoffs in this population have some support but a lower cutoff could result in an overclassification of depression in insomnia patients, a documented problem in the clinical literature. Understanding which items discriminate insomnia patients without depression may help address this nosological issue.
authors.affiliation: Department of Psychology, Ryerson University, 350 Victoria Street, JOR1037, Toronto, Ontario, Canada.
authors.forename: Colleen E
authors.initials: CE
authors.lastname: Carney
authors.forename: Christi
authors.initials: C
authors.lastname: Ulmer
authors.forename: Jack D
authors.initials: JD
authors.lastname: Edinger
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Krystal
authors.forename: Faye
authors.initials: F
authors.lastname: Knauss
mesh_terms: D000704:Analysis of Variance; D015897:Comorbidity; D003866:Depressive Disorder / Q000175:diagnosis* / Q000453:epidemiology* / Q000523:psychology; D005260:Female; D006801:Humans; D007406:Interview, Psychological / Q000379:methods; D008297:Male; D008875:Middle Aged; D017286:Polysomnography / Q000379:methods; D011569:Psychiatric Status Rating Scales / Q000592:standards*; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D007319:Sleep Initiation and Maintenance Disorders / Q000175:diagnosis / Q000453:epidemiology* / Q000523:psychology*